In closed-loop multiple input multiple output (MIMO) beamforming, a subscriber station (SS) quantizes the ideal beamforming matrix and sends the quantization index back to a base station (BS). The BS reconstructs the beamforming matrix according to the feed back index and conducts the beamforming. It is well known that the beamforming increases the link performance and system throughput.
Although the present invention is not limited in this respect, in 802.16e (WiMAX), the ideal beamforming matrix is quantized by a constant quantization codebook. The codebook is optimized for a single channel scenario, where the transmit antenna correlation at the BS is zero. However, the transmit antenna correlation is not constantly zero in reality and varies with several factors such as the antenna spacing at the BS, the BS antenna height, LOS/NLOS condition, BS and SS separation. Furthermore, the optimal quantization codebook varies with the antenna correlation, and thus it is desirable to adapt the codebook to the correlation. For example, the discrete Fourier transform (DFT) codebook and the 802.16e codebook are optimized for either the high or the low antenna correlations but not both. Fortunately, the antenna correlation varies very slowly as compared to the short-term channel fading, and there is a feedback mechanism for long term information in 802.16e.
Thus, a strong need exists for techniques utilizing adaptive codebooks for beamforming in wireless networks.
It will be appreciated that for simplicity and clarity of illustration, elements illustrated in the figures have not necessarily been drawn to scale. For example, the dimensions of some of the elements are exaggerated relative to other elements for clarity. Further, where considered appropriate, reference numerals have been repeated among the figures to indicate corresponding or analogous elements.